Image segmentation is the process of delineating structures of interest from a given image. This involves labeling objects in image or finding boundaries enclosing different organs in images. The segmentation of the organs is prerequisite to estimate the organ characteristics. The derived organ characteristics can be used for quantitative analysis of the organ including disease diagnosis. For example, in cardiac domain, the organ of interest can be left and right ventricle and the characteristics could be ejection fraction, myocardial motion, ventricle volumes, and/or others. These characteristics could be used for quantitative analysis of cardiac function as well as diagnosis of various cardiac diseases. In another example, in retinal imaging domain, the organ of interest could be optic cup and optic disc and the characteristics could be cup-to-disc-ratio and notching. These characteristics could be used to diagnose the glaucoma disease. In clinical studies the segmentation task is often performed manually, which is not only tedious and time-consuming but also suffers from inter and intra-observer variability.